Distributed Energy Resources, Virtual Power Plants, and the Smart Grid

The specific focus of this Article is on the virtual power plant (VPP) concept, an intriguing idea that involves an aggregation of DERs to provide a fleet of resources that can serve as the functional equivalent of a traditional power plant. As the name suggests, this fleet of DERs can add up in the aggregate to the equivalent of a significant resource. Under certain conditions, this resource can be used on the grid (i.e., dispatched) much as a conventional power plant would be. This could reduce demand for fossil fuel-fired plants by enabling a utility to avoid generating electricity or purchasing it in wholesale markets. Increased availability of DR can also help with the integration of DG into the grid. If it is predictable and controllable, it can be called upon by a utility or wholesale market to facilitate DG integration by smoothing out the peaks and valleys of demand for electricity, counterbalancing the inherent variability of DG sources such as solar and wind. Research and early pilot projects are testing the VPP concept, and several utilities are embarking on plans to deploy VPPs more broadly. This Article describes one such deployment, the VPP project underway at the San Antonio, Texas-based utility CPS Energy.26 When complete, the CPS VPP will use the advanced technologies and two-way communications capabilities of the Smart Grid ( smart meters and associated software and hardware) to link together up to 140,000 homes and provide DR equivalent to the output of a 250 megawatts (MW) power plant. The CPS Energy pilot and others will test the fleet of resources concept and may yield valuable information to guide its expansion elsewhere. In Part II, this Article discusses the concept of demand response and its relationship to Smart Grid technologies. Part III discusses the specific challenges of integrating DERs into the grid, focusing on the potential for DR to help integrate the large number of DG sources expected to come on line in the future into the grid, and specifically on the concept of regulation, or frequency control of the grid. Parts IV and V analyze the VPP concept, with specifics about the CPS Energy program, and a description of challenges facing the expansion of the VPP concept elsewhere

Reactive Power Procurement: Lessons from Three Leading Countries

This paper explores the international experience in the procurement of reactive power and related electricity ancillary services. It involves system operators from different jurisdictions including Australia, the United States and Great Britain. The paper evaluates the different procurement mechanisms and related compensation schemes. In addition, it also appraises a novel approach (from the Power Potential initiative in the UK) for contracting reactive power services from distributed energy resources (DERs) using a market-based mechanism. The conceptual auction design applicable to the procurement of reactive power is also discussed. Our findings suggest that competition in reactive power is very limited in comparison with other ancillary services such as frequency regulation and capacity reserves. The introduction of more market oriented mechanisms for acquiring reactive and active power services by the system operator opens new opportunities and new ways to deal with voltage stability issues. Power Potential trails a technical and commercial solution, new market roles and the new interactions required in the introduction of a competitive reactive power market

The Value of Vehicle-to-Grid Systems in the Clean Energy Transition: Policy and Regulatory Issues

As the United States transitions to clean energy, advances in technology are making such a transition possible by enabling utility-scale renewable energy generation (primarily wind and solar) and transportation electrification. However, the growth in renewable energy generation and electric vehicles (EVs) has created new reliability issues for the electric grid due to the intermittent nature of solar and wind power and increased load on the grid from EV charging. New methods and tools are needed to balance energy supply and demand. One such tool is the vehicle-to-grid (V2G) system, which uses EV batteries to help balance the grid, providing additional value beyond transportation and contributing to the clean energy transition. This article advocates for the use of V2G at scale and surveys the policy, technology, and regulatory issues involved in making it successful. Part I argues that V2G should be used as part of the clean energy transition to address renewable generation reliability issues, reduce the grid strain caused by increased EV charging, and expand storage resources for the electric grid. Part II explains how several technology and infrastructure barriers to V2G viability have been reduced or eliminated and discusses issues that still require resolution. Part III makes policy and regulatory recommendations for integrating V2G into grids operating in vertically integrated, monopoly markets or in restructured markets and for resolving two issues central to V2G grid integration: ownership and compensation

Federal Regulatory Barriers to Grid-Deployed Energy Storage

Until recently, the most advanced form of grid-deployed energy storage involved pumping water up a hill. But “newer storage technologies like flywheels and chemical batteries have recently achieved technological maturity and are well into successful pilot stages and, in some cases, commercial operation”. If widely adopted these new energy storage technologies will fundamentally alter the operation of our electricity syste

Loads Providing Ancillary Services: Review of International Experience

In this study, we examine the arrangements for and experiences of end-use loads providing ancillary services (AS) in five electricity markets: Australia, the United Kingdom (UK), the Nordic market, and the ERCOT and PJM markets in the United States. Our objective in undertaking this review of international experience was to identify specific approaches or market designs that have enabled customer loads to effectively deliver various ancillary services (AS) products. We hope that this report will contribute to the ongoing discussion in the U.S. and elsewhere regarding what institutional and technical developments are needed to ensure that customer loads can meaningfully participate in all wholesale electricity markets

SEEV4City INTERIM 'Summary of the State of the Art' report

This report summarizes the state-of-the-art on plug-in and full battery electric vehicles (EVs), smart charging and vehicle to grid (V2G) charging. This is in relation to the technology development, the role of EVs in CO2 reduction, their impact on the energy system as a whole, plus potential business models, services and policies to further promote the use of EV smart charging and V2G, relevant to the SEEV4-City project

Power allocation and user selection in multi-cell: multi-user massive MIMO systems

Submitted in fulfilment of the academic requirements for the degree of Master of Science (Msc) in Engineering, in the School of Electrical and Information Engineering (EIE), Faculty of Engineering and the Built Environment, at the University of the Witwatersrand, Johannesburg, South Africa, 2017The benefits of massive Multiple-Input Multiple-Output (MIMO) systems have made it a solution for future wireless networking demands. The increase in the number of base station antennas in massive MIMO systems results in an increase in capacity. The throughput increases linearly with an increase in number of antennas. To reap all the benefits of massive MIMO, resources should be allocated optimally amongst users. A lot of factors have to be taken into consideration in resource allocation in multi-cell massive MIMO systems (e.g. intra-cell, inter-cell interference, large scale fading etc.) This dissertation investigates user selection and power allocation algorithms in multi-cell massive MIMO systems. The focus is on designing algorithms that maximizes a particular cell of interest’s sum rate capacity taking into consideration the interference from other cells. To maximize the sum-rate capacity there is need to optimally allocate power and select the optimal number of users who should be scheduled. Global interference coordination has very high complexity and is infeasible in large networks. This dissertation extends previous work and proposes suboptimal per cell resource allocation models that are feasible in practice. The interference is introduced when non-orthogonal pilots are used for channel estimation, resulting in pilot contamination. Resource allocation values from interfering cells are unknown in per cell resource allocation models, hence the inter-cell interference has to be modelled. To tackle the problem sum-rate expressions are derived to enable power allocation and user selection algorithm analysis. The dissertation proposes three different approaches for solving resource allocation problems in multi-cell multi-user massive MIMO systems for a particular cell of interest. The first approach proposes a branch and bound algorithm (BnB algorithm) which models the inter-cell interference in terms of the intra-cell interference by assuming that the statistical properties of the intra-cell interference in the cell of interest are the same as in the other interfering cells. The inter-cell interference is therefore expressed in terms of the intra-cell interference multiplied by a correction factor. The correction factor takes into consideration pilot sequences used in the interfering cells in relation to pilot sequences used in the cell of interest and large scale fading between the users in the interfering cells and the users in the cell of interest. The resource allocation problem is modelled as a mixed integer programming problem. The problem is NP-hard and cannot be solved in polynomial time. To solve the problem it is converted into a convex optimization problem by relaxing the user selection constraint. Dual decomposition is used to solve the problem. In the second approach (two stage algorithm) a mathematical model is proposed for maximum user scheduling in each cell. The scheduled users are then optimally allocated power using the multilevel water filling approach. Finally a hybrid algorithm is proposed which combines the two approaches described above. Generally in the hybrid algorithm the cell of interest allocates resources in the interfering cells using the two stage algorithm to obtain near optimal resource allocation values. The cell of interest then uses these near optimal values to perform its own resource allocation using the BnB algorithm. The two stage algorithm is chosen for resource allocation in the interfering cells because it has a much lower complexity compared to the BnB algorithm. The BnB algorithm is chosen for resource allocation in the cell of interest because it gives higher sum rate in a sum rate maximization problem than the two stage algorithm. Performance analysis and evaluation of the developed algorithms have been presented mainly through extensive simulations. The designed algorithms have also been compared to existing solutions. In general the presented results demonstrate that the proposed algorithms perform better than the existing solutions.XL201